Computer vision's repositories
FixRes
This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423
snorkel
A system for quickly generating training data with weak supervision
jetson-inference
Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
simrdwn
Rapid satellite imagery object detection
CMUComputationalPhotography
Jupyter Notebooks for CMU Computational Photography Course 15.463
ssd_detectors
SSD-based object and text detection with Keras, SSD, DSOD, TextBoxes, SegLink, TextBoxes++, CRNN
Deep-Learning-Approach-for-Surface-Defect-Detection
(最先进的缺陷检测网络) A Tensorflow implementation of "Segmentation-Based Deep-Learning Approach for Surface-Defect Detection"
Lightweight-Segmentation
Lightweight models for real-time semantic segmentation(include mobilenetv1-v3, shufflenetv1-v2, igcv3, efficientnet).
Retinaface
Retinaface windows
deep-face-alignment
The MXNet Implementation of Stacked Hourglass and Stacked SAT for Robust 2D and 3D Face Alignment
SENet
Squeeze-and-Excitation Networks
High-Performance-Face-Recognition
🔥🔥Several High-Performance Models for Unconstrained/Large-Scale/Low-Shot Face Recognition🔥🔥
pytorch-inference
PyTorch 1.0 inference in C++ on Windows10 platforms
MC-GAN
Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018
paper-reading
Notes about papers I read (in Japanese)
awesome-xamarin-forms
A curated list of awesome Xamarin.Forms libraries and resources
Face-Pose-Net
Estimate 3D face pose (6DoF) or 11 parameters of 3x4 projection matrix by a Convolutional Neural Network
awesome-ai-infrastructures
Infrastructures™ for Machine Learning Training/Inference in Production.
Deep-Learning-in-Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
deepstream-plugins
Samples for TensorRT/Deepstream for Tesla & Jetson
dl-inference-server
Deep Learning Inference Server Clients
machinelearning-1
ML.NET is an open source and cross-platform machine learning framework for .NET.
awesome-Face_Recognition
papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;
EasyAI
AI platform for everyone
DeepLearning-500-questions
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06
mobileFacenet-ncnn
implementation of nccnn's mobileFacenet
DeepSpeech
A TensorFlow implementation of Baidu's DeepSpeech architecture
MVision
机器人视觉 无人驾驶 视觉SLAM ORB LSD SVO DSO 深度学习目标检测yolov3 行为检测 opencv PCL 双目视觉
awesome-nlp
:book: A curated list of resources dedicated to Natural Language Processing (NLP)